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ATLAS.ti-The Qualitative Data Analysis Software
Making Sense of Research Data in Policy Analysis




Jörg Hecker | ATLAS.ti GmbH . May 2011.
Agenda


01. Applications                          05. Is team work possible?
02. Central concept: the Hermeneutic
   Unit (HU)                              06. How can data be
                                            exported?
03. Project Elements:
   primary documents
   quotations
   codes
   memos
   families
   networks

04. What kinds of questions to ask?



Jörg Hecker | ATLAS.ti GmbH . May 2011.
Applications in Policy Research

• It can be used in any research phase of the policy cycle, such as needs
  assessments, social impact assessments, and process/formative/outcome
  evaluations.

• It assists researchers in the process of identifying and making sense of
  people‘s points of view and perspectives on issues.

• It allows for rich analysis of complex studies involving different sources of
  information.

• It allows for the study of single cases as well as for comparative studies
  across cases.

•     It provides evidence to support decision-making processes.

• The researcher is always in control: methodological freedom (from
  hypothesis-testing to grounded theory).
Jörg Hecker | ATLAS.ti GmbH . May 2011.
Central Concept: Hermeneutic Unit (HU)



• This is your project

• Container that holds
the sources of information
and all of the analytical
work done around them.

Picture: All data sources (Text
Image. Video..)




     Jörg Hecker | ATLAS.ti GmbH . May 2011.
Project elements: Primary Documents


•   Sources of information to be analyzed (no
    limit in terms of quantity).
•   Triangulate different methods of data
    collection, such as:
      – Structured, semi-structured, and
          unstructured interviews
      – Focus groups
      – Surveys with open-ended questions
      – Field notes from observations
      – Archival sources: institutional records,
          websites, e-mails, blogs, etc.
      – Literature reviews
      – Drawing and pictures

•   Accepts documents in different formats:
     – Text: Word, RTF, PDF, TXT
     – Survey in Excel
     – Audio
     – Video
     – Image
     – Google Earth


      Jörg Hecker | ATLAS.ti GmbH . May 2011.
Project elements: Quotations



•   Segments of data that the
    researcher selects according to
    research interests.
•   Quotations can be as short as a
    single character and as long as the
    entire primary document.
•   Quotations are always shown
    within their larger context.
•   The content of Quotations can be
    exported as Rich Text and HTML
    files.




     Jörg Hecker | ATLAS.ti GmbH . May 2011.
Project elements: Codes


• Concepts that can either derive from
external frameworks of reference or
emerge from the text.
•Codes can be grouped according to shared
conceptual characteristics (eg., all codes
that respond to specific topic).
• Codes can be linked to quotations by the
researcher or automatically by the system
(auto-coding).
• Codes can be commented (operational
definitions).
• All codes can easily be accessed via the
Code Manager.




   Jörg Hecker | ATLAS.ti GmbH . May 2011.
Project elements: Memos




 • Spaces for reflection.
 • This is where the analyst brings
 together what has been discovered,
 described, and analyzed.
 • Memos can be linked to quotations,
 codes, and other memos.
 •A good memo (or a good system of
 memos) can become the basis for the
 research report.




Jörg Hecker | ATLAS.ti GmbH . May 2011.
Project elements: Families


• The Project Elements can be grouped
according to shared characteristics.
• Primary document families: group
documents according to specific
attributes, such as demographic (e.g.,
age, gender, ethnicity), sites (e.g.,
Belfast, London, Berlin), and waves of
data collection (e.g, first wave, second
wave). Thus, the researcher can explore
the data looking for similarities and
differences across groups.
• Code families: group codes according to
shared conceptual characteristics, such as
codes representing the point of view of
the participant, codes related to a specific
research objective, codes that represent a
given hypothesis. Thus, the researcher can
explore the data looking for similarities
and differences across conceptual groups.
• Memo families: group memos according
to shared characteristics, such as memos
exploring the findings related to a given
research objective or hypothesis, memos
reflecting upon the method of analysis, or
memos analyzing the literature.



Jörg Hecker | ATLAS.ti GmbH . May 2011.
Project elements: Network Views



• Graphical representations
showing linkages between
objects of the HU (like
conceptual maps).

• Networks are given by default
by the system (weak link
networks) *

•Networks can be semantic
(strong link networks), such as
those connecting codes through
a given meaning (e.g., is part of,
is a, is associated with)**




Jörg Hecker | ATLAS.ti GmbH . May 2011.
What kinds of questions to ask?

 • What themes are found in the data?
 • What themes are more/less relevant
 from a quantitative perspective?
 • What is the qualitative relevance of
 themes? Does it vary accross cases,
 participants, or waves of data collection?
 • Whenever study participants talk about
 Theme X, what else are they talking
 about?
 • What is the context within which
 participants talk about Theme X?
 •What do participants say about Theme X
 AND/OR Theme Y? Any variation across
 cases, participants, or waves of data
 collection?
 •How does the literature/theory inform
 the study‘s findings?
 • Is there enough evidence in the data to
 support a given hypothesis?
 • How do data from archival research
 inform/complement primary data?



Jörg Hecker | ATLAS.ti GmbH . May 2011.
Is team work possible?

• Each team member can be in
charge of coding a specific set of
primary documents.
• Each team member can be in
charge of exploring a specific
conceptual domain.
• No limit in terms of the number
of people working in different
aspects of the analysis in a team
setting.
• Need for strong coordination
and transparency in
collaboration.
• Inter-rater reliability can be
calculated using CAT (Steward
Shulman)




Jörg Hecker | ATLAS.ti GmbH . May 2011.
How can data be exported?

• XML
• HTML
• SPSS
• Excel
• Rich Text
Format (RTF)
• PDF
• Graphic formats




Jörg Hecker | ATLAS.ti GmbH . May 2011.
Thank you!
ATLAS.ti Scientific Software Development GmbH
Hardenbergstr. 7
D-10623 BERLIN
Tel +49 30 31 99 88 971
Fax +49 30 31 99 88 979




Jörg Hecker | ATLAS.ti GmbH . May 2011.
Presented at the 2nd European
conference on Qualitative Research for
Policy Making, 26 -27 May 2011, Belfast



              For more information
       Please visit: http://www.merlien.org

Jörg Hecker | ATLAS.ti GmbH . May 2011.

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Atlas.ti making sense of research data in policy analysis

  • 1. ATLAS.ti-The Qualitative Data Analysis Software Making Sense of Research Data in Policy Analysis Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 2. Agenda 01. Applications 05. Is team work possible? 02. Central concept: the Hermeneutic Unit (HU) 06. How can data be exported? 03. Project Elements: primary documents quotations codes memos families networks 04. What kinds of questions to ask? Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 3. Applications in Policy Research • It can be used in any research phase of the policy cycle, such as needs assessments, social impact assessments, and process/formative/outcome evaluations. • It assists researchers in the process of identifying and making sense of people‘s points of view and perspectives on issues. • It allows for rich analysis of complex studies involving different sources of information. • It allows for the study of single cases as well as for comparative studies across cases. • It provides evidence to support decision-making processes. • The researcher is always in control: methodological freedom (from hypothesis-testing to grounded theory). Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 4. Central Concept: Hermeneutic Unit (HU) • This is your project • Container that holds the sources of information and all of the analytical work done around them. Picture: All data sources (Text Image. Video..) Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 5. Project elements: Primary Documents • Sources of information to be analyzed (no limit in terms of quantity). • Triangulate different methods of data collection, such as: – Structured, semi-structured, and unstructured interviews – Focus groups – Surveys with open-ended questions – Field notes from observations – Archival sources: institutional records, websites, e-mails, blogs, etc. – Literature reviews – Drawing and pictures • Accepts documents in different formats: – Text: Word, RTF, PDF, TXT – Survey in Excel – Audio – Video – Image – Google Earth Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 6. Project elements: Quotations • Segments of data that the researcher selects according to research interests. • Quotations can be as short as a single character and as long as the entire primary document. • Quotations are always shown within their larger context. • The content of Quotations can be exported as Rich Text and HTML files. Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 7. Project elements: Codes • Concepts that can either derive from external frameworks of reference or emerge from the text. •Codes can be grouped according to shared conceptual characteristics (eg., all codes that respond to specific topic). • Codes can be linked to quotations by the researcher or automatically by the system (auto-coding). • Codes can be commented (operational definitions). • All codes can easily be accessed via the Code Manager. Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 8. Project elements: Memos • Spaces for reflection. • This is where the analyst brings together what has been discovered, described, and analyzed. • Memos can be linked to quotations, codes, and other memos. •A good memo (or a good system of memos) can become the basis for the research report. Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 9. Project elements: Families • The Project Elements can be grouped according to shared characteristics. • Primary document families: group documents according to specific attributes, such as demographic (e.g., age, gender, ethnicity), sites (e.g., Belfast, London, Berlin), and waves of data collection (e.g, first wave, second wave). Thus, the researcher can explore the data looking for similarities and differences across groups. • Code families: group codes according to shared conceptual characteristics, such as codes representing the point of view of the participant, codes related to a specific research objective, codes that represent a given hypothesis. Thus, the researcher can explore the data looking for similarities and differences across conceptual groups. • Memo families: group memos according to shared characteristics, such as memos exploring the findings related to a given research objective or hypothesis, memos reflecting upon the method of analysis, or memos analyzing the literature. Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 10. Project elements: Network Views • Graphical representations showing linkages between objects of the HU (like conceptual maps). • Networks are given by default by the system (weak link networks) * •Networks can be semantic (strong link networks), such as those connecting codes through a given meaning (e.g., is part of, is a, is associated with)** Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 11. What kinds of questions to ask? • What themes are found in the data? • What themes are more/less relevant from a quantitative perspective? • What is the qualitative relevance of themes? Does it vary accross cases, participants, or waves of data collection? • Whenever study participants talk about Theme X, what else are they talking about? • What is the context within which participants talk about Theme X? •What do participants say about Theme X AND/OR Theme Y? Any variation across cases, participants, or waves of data collection? •How does the literature/theory inform the study‘s findings? • Is there enough evidence in the data to support a given hypothesis? • How do data from archival research inform/complement primary data? Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 12. Is team work possible? • Each team member can be in charge of coding a specific set of primary documents. • Each team member can be in charge of exploring a specific conceptual domain. • No limit in terms of the number of people working in different aspects of the analysis in a team setting. • Need for strong coordination and transparency in collaboration. • Inter-rater reliability can be calculated using CAT (Steward Shulman) Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 13. How can data be exported? • XML • HTML • SPSS • Excel • Rich Text Format (RTF) • PDF • Graphic formats Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 14. Thank you! ATLAS.ti Scientific Software Development GmbH Hardenbergstr. 7 D-10623 BERLIN Tel +49 30 31 99 88 971 Fax +49 30 31 99 88 979 Jörg Hecker | ATLAS.ti GmbH . May 2011.
  • 15. Presented at the 2nd European conference on Qualitative Research for Policy Making, 26 -27 May 2011, Belfast For more information Please visit: http://www.merlien.org Jörg Hecker | ATLAS.ti GmbH . May 2011.